NVIDIA is hiring engineers to scale up its AI Infrastructure. We expect you to have a strong programming background, a deep understanding of distributed systems, familiarity with software testing and deployment, and excellent communication and planning abilities. We also welcome out-of-the-box thinkers who can provide new ideas with strong at execution bias. Expect to be constantly challenged, improving, and evolving for the better. You and other engineers in this team will help advance NVIDIA's capacity to build and deploy leading infrastructure solutions for a broad range of AI-based applications that affect core data science. What are you waiting for if you're creative, passionate about what you do, and love having fun apply today!
We’re looking for a highly motivated, creative engineer with strong experience in system software to join the DGX Cloud Software Team. You will lead the architecture, design and implementation of our next generation DGX cloud clusters using latest technologies. On this team, you will do full stack deployment including hardware architecture, workload orchestration and application performance tuning. Are you ready to change the next generation of computing? Join us at the forefront of technological advancement.
What you’ll be doing:
Lead technical activities for data centers with focus on hybrid deployments between cloud and on-prem
Providing expertise in infrastructure workflows, including hardware, software release, workload orchestration and application tuning
Provide fast and creative solutions for complex problems and write effective, clear and reliable architecture specification
Translate requirements to vision, architecture and roadmap
Work with engineering teams across NVIDIA to ensure your software integrates seamlessly from the hardware all the way up to the AI training applications.
What we need to see:
Masters or PhD in Computer Science, Computer Engineering, Physics or equivalent experience.
9+ years of experience in this field.
Data Sciences, Deep Learning, or Machine Learning coursework
Ability to seamlessly shift between Linux system environments to Python programming
Programming skills in 1 or more high-level languages (C, C++, Go, Rust, etc)
System-level experience with both hardware and software
Motivated self-starter with an equal balance of strong problem-solving skills and customer-facing communication skills
Strong design, coding, analytical, debugging and problem-solving skills
Passion for continuous learning and knowledge transfer. Ability to work concurrently with multiple groups locally and abroad in the organization
Ways to stand out from the crowd:
Experience with GPU deep learning and data sciences. Experience using TensorFlow, PyTorch or other DL framework. Experience working with Docker containers, Slurm, Terraform and Kubernetes
CUDA programming and NCCL experience. HPC programming experience including MPI, OpenACC, or other parallel programming tools. Hands-on experience with DGX Cloud, NVIDIA AI Enterprise AI Software, Base Command Manager, NEMO and NVIDIA Inference Microservices.
Interest in crafting, analyzing and fixing large-scale distributed systems.
Systematic problem-solving approach, coupled with strong communication skills and a sense of ownership and drive.
You will also be eligible for equity and benefits.
Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
